Strategies to enable the reopening of businesses and schools in countries emerging from social-distancing measures revolve around knowledge of who has COVID-19 or is displaying recognized symptoms, the people with whom they have had physical contact, and which groups are most likely to experience adverse outcomes. Efforts to clarify these issues are drawing on the collection and use of large datasets about peoples' movements and their health. In this Comment, we outline the importance of earning social license for public approval of big data initiatives, and specify principles of data law and data governance practices that can promote social license. We provide illustrative examples from the United States, Canada, and the United Kingdom.Technological advances in multimodal wearable and connected devices have enabled the measurement of human movement and physiology in naturalistic settings. The ability to collect continuous activity monitoring data with digital devices in real-world environments has opened unprecedented opportunity to establish clinical digital phenotypes across diseases. Many traditional assessments of physical function utilized in clinical trials are limited because they are episodic, therefore, cannot capture the day-to-day temporal fluctuations and longitudinal changes in activity that individuals experience. In order to understand the sensitivity of gait speed as a potential endpoint for clinical trials, we investigated the use of digital devices during traditional clinical assessments and in real-world environments in a group of healthy younger (n?=?33, 18-40 years) and older (n?=?32, 65-85 years) adults. We observed good agreement between gait speed estimated using a lumbar-mounted accelerometer and gold standard system during the performance of traditional gait assessment task in-lab, and saw discrepancies between in-lab and at-home gait speed. We found that gait speed estimated in-lab, with or without digital devices, failed to differentiate between the age groups, whereas gait speed derived during at-home monitoring was able to distinguish the age groups. Furthermore, we found that only three days of at-home monitoring was sufficient to reliably estimate gait speed in our population, and still capture age-related group differences. https://www.selleckchem.com/products/asunaprevir.html Our results suggest that gait speed derived from activities during daily life using data from wearable devices may have the potential to transform clinical trials by non-invasively and unobtrusively providing a more objective and naturalistic measure of functional ability.There has been a proliferation of urban high-level trauma centers. The aim of this study was to describe the density of high-level adult trauma centers in the 15 largest cities in the USA and determine whether density was correlated with urban social determinants of health and violence rates.
The largest 15 US cities by population were identified. The American College of Surgeons' (ACS) and states' department of health websites were cross-referenced for designated high-level (levels 1 and 2) trauma centers in each city. Trauma centers and associated 20?min drive radius were mapped. High-level trauma centers per square mile and per population were calculated. The distance between high-level trauma centers was calculated. Publicly reported social determinants of health and violence data were tested for correlation with trauma center density.
Among the 15 largest cities, 14 cities had multiple high-level adult trauma centers. There was a median of one high-level trauma center per every 150 square kilometers with a range of one center per every 39 square kilometers in Philadelphia to one center per596 square kilometers in San Antonio. There was a median of one high-level trauma center per 285?034 people with a range of one center per 175?058 people in Columbus to one center per 870?044 people in San Francisco. The median minimum distance between high-level trauma centers in the 14 cities with multiple centers was 8 kilometers and ranged from 1 kilometer in Houston to 43 kilometers in San Antonio. Social determinants of health, specifically poverty rate and unemployment rate, were highly correlated with violence rates. However, there was no correlation between trauma center density and social determinants of health or violence rates.
High-level trauma centers density is not correlated with social determinants of health or violence rates.
VI.
Economic/decision.
Economic/decision.Africa accounts forabout 90% of the global trauma burden. Mapping evidence on health systemfactors associated with post-trauma mortality is essential in definingpre-hospital care research priorities and mitigation of the burden. The studyaimed to map and synthesize existing evidence and research gaps on healthsystem factors associated with post-trauma mortality at the pre-hospital carelevel in Africa.
A scoping review of published studies and grey literature was conducted. The search strategy utilized electronic databases comprising of Medline, Google Scholar, Pub-Med, Hinari and Cochrane Library. Screening and extraction of eligible studies was done independently and in duplicate.
A total of 782 study titles and or abstracts were screened. Of these, 32 underwent full text review. Out of the 32, 17 met the inclusion criteria for final review. The majority of studies were literature reviews (24%) and retrospective studies (23%). Retrospective and qualitative studies comprised 6% of the included studies, ed method approaches. Moreover, similar reviews incorporating other LMICs are also warranted. Key Words Health System Factors, Emergency Medical Services [EMS], Pre-hospital Care, Post-Trauma mortality, Africa.Obstructive sleep apnea (OSA) is increasingly prevalent in the range of 2% to 24% in the US population. OSA is a well-described predictor of pulmonary complications after elective operation. Yet, data are lacking on its effect after operations for trauma. We hypothesized that OSA is an independent predictor of pulmonary complications in patients undergoing operations for traumatic pelvic/lower limb injuries (PLLI).
Nationwide Inpatient Sample (2009-2013) was queried for International Classification of Diseases, Ninth Revision, Clinical Modification codes for PLLI requiring operation. Elective admissions and those with concurrent traumatic brain injury with moderate to prolonged loss of consciousness were excluded. Outcome measures were pulmonary complications including ventilatory support, ventilator-associated pneumonia, pulmonary embolism (PE), acute respiratory distress syndrome (ARDS), and respiratory failure. Multivariable logistic regression analysis was used, adjusting for OSA, age, sex, race/ethnicity, and specific comorbidities (obesity, chronic lung disease, and pulmonary circulatory disease).